Unsupervised domain adaptation by backpropagation
Y Ganin, V Lempitsky - International conference on machine …, 2015 - proceedings.mlr.press
… Unlike most previous papers on domain adaptation that worked with fixed feature … domain
adaptation and deep feature learning within one training process (deep domain adaptation). …
adaptation and deep feature learning within one training process (deep domain adaptation). …
Open set domain adaptation by backpropagation
… in unsupervised domain adaptation. One of the effective methods for unsupervised domain
adaptation are … Each domain has unique characteristics of their features, which decrease the …
adaptation are … Each domain has unique characteristics of their features, which decrease the …
Unsupervised domain adaptation with residual transfer networks
… This paper addresses unsupervised domain adaptation within deep networks for jointly
learning transferable features and adaptive classifiers. We extend deep convolutional networks (…
learning transferable features and adaptive classifiers. We extend deep convolutional networks (…
Deep reconstruction-classification networks for unsupervised domain adaptation
… In this paper, we propose a novel unsupervised domain adaptation algorithm based on
deep learning for visual object recognition. Specifically, we design a new model called Deep …
deep learning for visual object recognition. Specifically, we design a new model called Deep …
Improved open set domain adaptation with backpropagation
J Fu, X Wu, S Zhang, J Yan - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
… -domain discrepancy between the source and target domains, many domain adaptation
methods tried their best to extract domain… the purpose of unsupervised domain adaptation. In a …
methods tried their best to extract domain… the purpose of unsupervised domain adaptation. In a …
[PDF][PDF] Deep unsupervised domain adaptation: A review of recent advances and perspectives
… To counter this, unsupervised domain adaptation (UDA) is proposed as a viable solution
to migrate knowledge learned from a labeled source domain to unseen, heterogeneous, and …
to migrate knowledge learned from a labeled source domain to unseen, heterogeneous, and …
Unsupervised domain adaptation by backpropagation
CH Ho, X Gu, Y Qi - cseweb.ucsd.edu
… Unsupervised adaptation from MNIST to SVHN gives a failure example for this approach. …
Semi-supervised domain adaptation, ie when one is additionally provided with a small …
Semi-supervised domain adaptation, ie when one is additionally provided with a small …
Deep unsupervised convolutional domain adaptation
… the unsupervised domain adaptation … unsupervised domain adaptation from the convolutional
perspective and develop an attention transfer process for convolutional domain adaptation…
perspective and develop an attention transfer process for convolutional domain adaptation…
A survey of unsupervised deep domain adaptation
… of the deep learning methods that have been designed for unsupervised domain adaptation
[152… approaches to single-source homogeneous unsupervised deep domain adaptation. …
[152… approaches to single-source homogeneous unsupervised deep domain adaptation. …
Deep hashing network for unsupervised domain adaptation
H Venkateswara, J Eusebio… - Proceedings of the …, 2017 - openaccess.thecvf.com
… unsupervised domain adaptation based on hashing (DAH) that incorporates unsupervised
domain adaptation … hashing for the source (5) and unsupervised hashing for the target (7) in a …
domain adaptation … hashing for the source (5) and unsupervised hashing for the target (7) in a …
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